SUPPLEMENTARY FIGURE LEGENDS
Figure S1. Graphical representation of hypothetical
evolutionary scenarios of medfly using DIYABC-RF. The strategy focused
on testing hypotheses of colonisation routes from South Africa to Brazil
or South Africa to the rest of the sampling sites. A) Analysis 1, in
light grey, highlights the best fit Scenario. B) Analysis 2, using only
Scenarios 2, 4 and 5 (the highest CV values in Analysis 1). The best fit
scenario is highlighted in light blue. CV: corresponded to the
classification vote for each scenario obtained in the different
analyses.
Figure S2. Pairwise Fst values for the six populations
of medfly. All calculations were significant, abbreviations are based on
where populations are collected. SA, South Africa; SP, Spain; GR,
Greece; GU, Guatemala; BR, Brazil; AU, Australia.
Figure S3. AIC statistic plots where lower value indicates
optimal clustering. A) Optimal AIC estimation using the dataset with the
six populations. B) Optimal AIC estimation using only populations
collected in introduced range (i.e. SP, GR, GU, BR, AU). Delta K
estimation by Evanno method. C) Best delta K estimation using the
dataset with the six populations. D) Best delta K estimation using only
populations collected in introduced range (i.e. SP, GR, GU, BR, AU).
Figure S4. Clustering analysis using the 1907 SNPs. A) Group
assignment probability plot using K=3 based on DAPC analysis. The colour
of cells points out the probability of assigning a given sample (red:
high probability) and the blue crosses indicate the true group
assignment. The row labels are specimens ID and columns (clusters)
correspond to the population groups. B) Hierarchical clustering (Ward
clustering), SA: South Africa, BR: Brazil, OP: Other populations. Dark
red arrow is highlighting the specimen SA_8 assigned to the major
cluster formed by populations collected in the introduced region.
Figure S5. Projection of dataset (observed data) from the
training set on Linear Discriminant Analysis plots. C) Analysis 1, six
scenarios analysed individually. D) Analysis 2, three scenarios analysed
individually.
Figure S6. Tree cloud produced by DENSITREE from SNAPP
analysis. Left: tree cloud of the 15 consensus trees of Fig. 6.Right : tree cloud obtained by independent subsample set from the
six populations studied. Maximum-clade-credibility tree estimation is
shown in dark blue (most highly supported), red is the next most
supported, and green is the least supported. Maximum-clade-credibility
tree shown in the black right-angled tree with posterior probabilities
at nodes. Branch width is proportional to theta.
Figure S7. Plot of sequencing read depth for microbiota
database and the rarefaction curve.
Figure S8. Number of unique and shared ASVs across different
biogeographical regions. A) South Africa compared to Palearctic sampling
locations. B) South Africa compared to Neotropical sampling locations.
C) South Africa compared to Australia (Australasian).
Figure S9. Alpha diversity of medfly microbiome across six
sampling locations. Observed (number of ASVs present -species richness),
Shannon, Inverse Simpson and Pielou’s evenness diversity indexes.